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The clinical management of lung cancer (LC) patients with bone metastasis (BM) is still a significant challenge. This study aimed to explore the role of primary tumor resection (PTR) on survival outcome of LC patients with BM and to develop two web-based nomograms for predicting the overall survival (OS) of LC patients with BM who received PTR and those who did not. We enrolled LC patients with BM from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Propensity score matching (PSM) was then conducted to balance the baseline characteristics of covariates between patients in surgery and non-surgery groups. Next, Kaplan–Meier analysis with log-rank test was performed to evaluate the survival benefit of PTR before and after PSM methods and to explore the impact of surgical resection extent on the prognosis of LC patients with BM and clinical outcomes in patients with different metastatic patterns. Cox proportional hazard regression analysis was then applied to determine the independent prognostic factors for OS of patients receiving PTR and did not receiving PTR, respectively. Subsequently, we constructed two individualized nomograms for predicting the 12-, 18- and 24-months OS. Finally, receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were generated to evaluate discrimination, accuracy and clinical utility of the nomograms. A total of 7747 eligible patients were included in this analysis. The survival analysis revealed that PTR was closely associated with better survival outcome among LC patients with BM(P < 0.05), while the survival benefit of PTR was suboptimal in patients presented with multiple metastases(P > 0.05). Besides, lobectomy shows best survival benefit. Two nomograms were then constructed based on independent prognostic factors of patients in the surgery group and the non-surgery group. The ROC curves showed good discrimination of the two nomograms, with the area under curve (AUC) of each time point being higher than 0.7 in both the training set and testing set. The calibration curves also demonstrated satisfactory consistency between actual survival and nomogram-predicted OS of both nomograms. The DCA showed high benefit of nomogram in a clinical context. Moreover, the study population was stratified into three groups based on the scores of the nomogram, and the survival analysis showed that this prognostic stratification was statistically significant (p < 0.05). This study showed that surgical resection of the primary site strategy can prolong survival of LC patients with BM to some extent, depending on different sites of metastasis and highly selected patients. Furthermore, the web-based nomograms showed significant accuracy in predicting OS for patients with or without surgery, which may provide valuable insights for patients' counseling and individualized decision-making for clinicians. [ABSTRACT FROM AUTHOR]

Background: Recent studies have shown that inflammatory indicators are closely related to the prognosis of patients with hepatocellular carcinoma, and they can serve as powerful indices for predicting recurrence and survival time after treatment. However, the predictive ability of inflammatory indicators has not been systematically studied in patients receiving transarterial chemoembolization (TACE). Therefore, the objective of this research was to determine the predictive value of preoperative inflammatory indicators for unresectable hepatocellular carcinoma treated with TACE. Methods: Our retrospective research involved 381 treatment-naïve patients in 3 institutions, including the First Affiliated Hospital of Soochow University, Nantong First People's Hospital, and Nantong Tumor Hospital, from January 2007 to December 2020 that received TACE as initial treatment. Relevant data of patients were collected from the electronic medical record database, and the recurrence and survival time of patients after treatment were followed up. Least absolute shrinkage and selection operator (LASSO) algorithm was used to compress and screen the variables. We utilized Cox regression to determine the independent factors associated with patient outcomes and constructed a nomogram based on multivariate results. Finally, the nomogram was verified from discriminability, calibration ability, and practical applicability. Results: Multivariate analysis revealed that the levels of aspartate aminotransferase-to-platelet ratio index (APRI) and lymphocyte count were independent influential indicators for overall survival (OS), whereas the levels of platelet-to-lymphocyte ratio (PLR) was an independent influential index for progression. Nomograms exhibited an excellent concordance index (C-index), in the nomogram of OS, the C-index was 0.753 and 0.755 in training and validation cohort, respectively; and in the nomogram of progression, the C-index was 0.781 and 0.700, respectively. The time-dependent C-index, time-dependent receiver operating characteristic (ROC), and time-dependent area under the curve (AUC) of the nomogram all exhibited ideal discrimination ability. Calibration curves significantly coincided with the standard lines, which indicated that the nomogram had high stability and low degree of over-fitting. Decision curve analysis revealed a wider range of threshold probabilities and could augment net benefits. The Kaplan-Meier curves for risk stratification indicated that the prognosis of patients varied significantly between risk categories (P <.0001). Conclusions: The developed prognostic nomograms based on preoperative inflammatory indicators revealed high predictive accuracy for survival and recurrence. It can be a valuable clinical instrument for guiding individualized treatment and predicting prognosis. [ABSTRACT FROM AUTHOR]